Flexural improvement of reinforced concrete beams strengthened with self-prestressing shape memory alloys

Author:

Alkhairo Ahmed1ORCID,Oukaili Nazar1ORCID,Al-Mahaidi Riadh2

Affiliation:

1. University of Baghdad, Baghdad, Iraq

2. Swinburne University of Technology, Hawthorn, VIC, Australia

Abstract

The study reported here aims to investigate the application of shape memory alloys (SMAs) in the form of strips for strengthening cracked reinforced concrete (RC) beams. The study proposes an innovative technique for prestressing RC beams by utilizing the shape recovery property of the alloy. Nine full-scale RC beams with a length of 3.75 m and a cross-section of 200 mm × 300 mm were categorized into three groups based on the steel reinforcement ratio, and tested under static loading. Three RC beams were used as control specimens and the other six were retrofitted with either one layer or two layers of SMA strips. The beams to be strengthened were exposed to an initial applied load before the installation of the SMA strip to simulate the deterioration scenario. SMA strips were retrofitted on the soffits of the deteriorated beams and activated by applying temperature from an external heat source while the temperature-deflection-strain measurements were monitored. Specimens were tested again up to failure to evaluate the strength improvement of the retrofitted specimens. Beams retrofitted with one layer of SMA experienced a deflection recovery up to 2.3 mm upon activation and an additional service load of up to 62%, whereas beams retrofitted with two layers experienced a deflection recovery up to 2.8 mm and an additional service load of up to 95%. In general, the deflection recovery was proportional to the ratio of the total reinforcement ratio after strengthening to the initial reinforcement ratio before strengthening. Therefore, tested specimens with two SMA layers experienced less improvement than specimens with one SMA layer. Finally, the experimental results were evaluated with two analytical methods: ACI method and the non-linear sectional analysis proposed by Oukaili.

Publisher

SAGE Publications

Subject

Building and Construction,Civil and Structural Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3